Lightning Talk: Leveraging Large Scale Data Analytics on Cloud Foundry
summary
Proof-of-concept simulates three lab rooms with over a dozen sensors each emitting records every second or faster, routed through a Tau IoT gateway into a Dell EMC PowerEdge cluster and dumped to Hadoop for batch and MongoDB updated every 5s for real time. A Shiny dashboard is refactored into Cloud Foundry microservices using Python, encountering packaging and runtime friction — notably Python buildpack supports Python 2 only and WebSockets bound to port 443 — and ultimately deploys and updates live RPM and sensor state displays.
AI-written summary · about
related talks
32mBuilding Data-Driven IoT Apps on Cloud Foundry - Dormain Drewitz, Pivotal
17mKeynote: Cloud Foundry for the Internet of (Really Important) Things
13mLightning Talk: Highlights of the Snowflake Elastic Data Warehouse
01h 03mLightning Talks, sponsored by Capital One
32mCase Study of Batch Processing With Spring Cloud Data Flow Server in Cloud Foundry
30mDelivering the Power of Data Using Spring Cloud Data Flow - Gilbert Lau, Wayne Lund
01h 20mApps + Data + Cloud: What Does It All Mean?
14mBeyond the Fridge pt.1